My doctoral and postdoctoral training has focused on advanced signal processing techniques for the analysis of surface electromyographic (EMG) signals recorded during dynamic contractions. My work as Research Assistant Professor at the NeuroMuscular Research Center of Boston University has been oriented toward the development and application of EMG analysis techniques to real life situations (e.g., lifting and load carrying) of interest in ergonomics. The use of surface EMG in ergonomics has been limited in the past by the inability of traditional analysis techniques to extract spectral information from surface EMG signals that are recorded during dynamic contractions. Recent developments in EMG analysis have made techniques available that appear to overcome such limitations. My long-term goal is to establish a research career in electromyography by applying advanced EMG analysis techniques to ergonomics. The NeuroMuscular Research Center at Boston University provides an ideal place to pursue my career goals. The mentorship of Prof. Carlo J. De Luca and Prof. Serge H. Roy, the availability of laboratory space and equipment, and the opportunity for discussions with colleagues (e.g., Prof. Gerald Gottlieb, Prof. Lars Oddsson, who are well-know and respected scientists in areas related to the research herein proposed) are unique opportunities to motivate the success of the project. In addition, the mentorship of Dr. Lawrence Hettinger, director of human factors and ergonomics at Arthur D Little, constitutes a great help to ensure that this research project, and my future career goals, will give me the opportunity of addressing problems of paramount importance in ergonomics. The proposed research is to establish preliminary work toward the definition of standards for the assessment of non-keyboard input devices (computer mouse) using EMG-based methodologies. The work is based on establishing a relationship between time and frequency parameters of the EMG signal and the different designs of computer mice. The identification of different patterns of muscle use and localized fatigue for different input devices will lead to future studies to develop a user-friendly assessment procedure for application in the field of ergonomics. Future studies by the applicant will focus on utilizing the innovation to gain a better understanding of overuse injury mechanisms related to work tasks and the operation of devices in the workplace.